MS Defense by Erin Heidelberger

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College of Design – School of Architecture- Master’s Thesis Defense – Erin Heidelberger



Friday, July 16th at 3pm 


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Committee Members:

Dr. Tarek Rakha, Assistant Professor, School of Architecture, College of Design

Georgia Institute of Technology


Dr. John E Taylor, Professor, School of Civil and Environmental Engineering, College of Engineering

Georgia Institute of Technology    


Dr. Tianzhen Hong , Staff Scientist and Deputy Head of the Building Technologies Department

Lawrence Berkeley National Lab  


Title: Addressing Urban Building Energy Modeling (UBEM) Data Needs: A Case Study in a Low Resource Community



Urban Building Energy Modeling (UBEM) is a method of simulating the energy usage of a grouping of buildings, at the scale of a neighborhood or city, rather than the typical simulation of a single building. This can be a powerful tool to reduce current energy usage, through testing retrofit scenarios on the existing building stock, and to guide future planning efforts. This switch in simulation scales is crucial to move towards more sustainable and resilient cities. This thesis addresses data availability issues to inform UBEM studies, in all urban contexts, by establishing a list of readily available data sources as well as a multi-step, theoretical framework that can be used to gather the data required to run an accurate UBEM that considers the surrounding socioeconomic factors. This framework is demonstrated through a case study in the Grove Park neighborhood of Atlanta, Georgia. 110 single-family households were modeled. The results of the study analyze current energy use patterns, compare neighborhood-specific archetype definitions to default residential archetype templates, and investigate the neighborhood’s performance under future weather scenarios. The study shows that within a single neighborhood the energy use intensity (EUI) can vary by up to 92 kWh/m2 based on building envelope condition and occupancy patterns. Default archetype inputs can dramatically underestimate or overestimate the energy use of households in a low resource community. Investigating energy performance under both current and future weather scenarios allows for energy efficiency strategies that are beneficial to the neighborhood now while increasing future resiliency.  



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